Automatic welding is commonplace in industry today where autonomous welding machines are preprogrammed to accomplish repetitive tasks. Dimensional variations in welded parts, misalignment of welded parts, impurities in weld materials and perturbations that arise during the weld process can result in improper welds. Any defect in the weld can substantially reduce weld life, degrading product quality and durability. Additionally, the costs of repetitive weld defects that go unnoticed can multiply rapidly.
Weld integrity is not easily discerned, as defects are often hidden in the form of porosity, embrittlement, lack of fusion and lack of penetration. Additionally, the hostile weld environment and the speed of many weld processes make it difficult for an operator to thoroughly inspect a weld without reducing process throughput considerably.
Consequently, industry recognizes the importance of automated fault detection systems in weld processes that can thoroughly scrutinize the weld for hidden defects, and can keep up with the assembly process. Defects should be detected quickly such that the faulty parts can be discarded or repaired, and repeated faults should be diagnosed in their infancy and treated as welding process failures.
Several techniques for detecting improper welds are in the prior art. Conventional off-line techniques periodically take sample parts from the assembly process and analyze them, for example by attempting to break the weld itself. If the weld breaks before the material around the weld breaks, then the weld is assumed to be faulty. These off-line techniques have the disadvantage of slowing the entire 10 weld process and of only analyzing the sample--allowing many untested welds to pass through the system. By increasing the sampling rate, fewer welds can pass through without being tested, but more potentially useful parts are destroyed.
On-line techniques exist in the prior art. Some of these techniques use ultrasonic sensors to sample high frequency weld emissions. The high frequency signals are analyzed to discern weld integrity. The sensors used in these methods are expensive, prone to failure, require accurate positioning with respect to the weld site, and require precise calibration.
Many on-line methods sense and analyze the amplitude of airborne emissions from the weld during the weld process. Such amplitude methods are highly sensitive to the noise in the weld environment, which distorts the sensed signal amplitude and thereby undermines the integrity of the amplitude analysis. Additionally, these methods require precise calibration of the sensors, and can produce erroneous results if the weld conditions are not identical from part to part.